Abstract: An automatic speech recognition (ASR) system detects an endpoint of an utterance using the active hypotheses under consideration by a decoder. The ASR system calculates the amount of non-speech detected by a plurality of hypotheses and weights the non-speech duration by the probability of each hypotheses. When the aggregate weighted non-speech exceeds a threshold, an endpoint may be declared.

Abstract: Determining the end of an utterance for purposes of automatic speech recognition (ASR) may be improved with a system that provides early results and/or incorporates semantic tagging. Early ASR results of an incoming utterance may be prepared based at least in part on an estimated endpoint and processed by a natural language understanding (NLU) process while final results, based at least in part on a final endpoint, are determined. If the early results match the final results, the early NLU results are already prepared for early execution. The endpoint may also be determined based at least in part on the content of the utterance, as represented by semantic tagging output from ASR processing. If the tagging indicate completion of a logical statement, an endpoint may be declared, or a threshold for silent frames prior to declaring an endpoint may be adjusted.